Soybean Peroxidase‐Catalyzed Treatment of Azo Dyes with or without Fe° Pretreatment
Bibliographic record
Abstract
Representative azo dyes (Acid Blue 113 [AB113] and Direct Black 38 [DB38]) were treated in a single step with soybean peroxidase (SBP) and hydrogen peroxide (H2O2), or in two steps, zero-valent iron (Fe°) pretreatment followed SBP/H2O2. The purpose of this research was to compare both treatment processes and to determine which one was the optimal for degradation of each azo dye. For AB113, the preferred process was the single-step process, 1.0 mM AB113 required 2.5 mM H2O2, 1.5 U/mL SBP at pH 4.0 for ≥ 95% color and dye removal and 30% total organic carbon (TOC) removal. For DB38, due to the products formed after Fe° reduction, which are enzyme substrates (aniline and benzidine; two of four products) a two-step process was preferred, which allowed reduction in the required SBP and H2O2 concentrations by 5- and 2-fold, respectively, compared to a single-step treatment for ≥ 95% color, dye, and aniline/benzidine removal and 88% TOC removal.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".